Live cell imaging has become the standard for high-content analysis and drug discovery applications. The most common assays on live cells include viability, proliferation and cytotoxicity assays as cellular physiology and function are measured while responding to applied perturbations. Cellular and tissue viability assays are typically measured using exogenous vital dyes as biomarkers of membrane integrity and cellular metabolic activity. However, these techniques are invasive and potentially toxic, and often require fixing of the tissue or permeabilization of the membranes. Furthermore, the common format of high-content analysis and flow cytometry requires isolated cells, or cells distributed on flat hard surfaces.
The need to perform viability, cytoxicity and proliferation assays in three-dimensional (3D) tissue has become increasingly urgent, primarily because drug response in two dimensions (2D) is often not the same as drug response in biologically-relevant three dimensional culture. This is in part because genomic profiles are not preserved in primary monolayer cultures. There have been several studies that have tracked the expression of genes associated with cell survival, proliferation, differentiation and resistance to therapy that are expressed differently in 2D cultures relative to three-dimensional culture. For example, three-dimensional culture from cell lines of epithelial ovarian cancer, hepatocellular carcinoma or colon cancer display expression profiles more like those from tumor tissues than when grown in 2D. In addition, the three-dimensional environment of 3D culture presents different pharmacokinetics than 2D monolayer culture and produce differences in cancer drug sensitivities.
Multicellular resistance (MCR) is a process that occurs only in groups of cells or inside solid tumors. Standard two-dimensional chemosensitivity/resistance assays (CSRAs) have failed to measure the occurrence of MCR because monolayer cultures lack the natural morphology and cellular microenvironments of normal tissues. The present disclosure contemplates a new class of predictive screen that is fundamentally different than CSRAs because it uses 3D living-tissue rather than isolated cells. Cells thrive in three-dimensional environments and communicate with near and distant neighbors. It is now known that cells in 2D do not behave as cells do in 3D tissues, with different genetic expression profiles, different intercellular signaling, and different forces attaching them to their environment. Therefore, understanding relevant biological functions requires the capture of dynamical processes and motions in three dimensions.
There are many physiological and tumor micro-environmental causes of MCR. For instance, drugs can be chemically inactivated by the chemical environment inside the tissue. The low oxygen and nutrient concentrations inside tissue induce cellular quiescence in which cells exit the cell cycle and are no longer influenced by anti-proliferative cancer drugs, and hence require pro-apoptotic drugs that remain active in the hypoxic microenvironment. Chronic hypoxia inside avascular tumors selects for cellular phenotypes that have the ability to differentiate into multiple cell types. In addition, the hypoxic microenvironment induces the expression of hypoxia-inducible factor HIF-1α that participates in complex intracellular signaling cascades that cause cell cycle arrest or apoptosis, but also can promote cell survival as well as the epithelial-to-mesenchymal transition (EMT). It is notable that hypoxia plays at least some role in all of these causes of MCR and has become a major focus of current cancer research, both in terms of evolution of metastatic virulence and therapeutics.
A barrier to progress has been the lack of a 3D biologically functional assay that is able to extract information from inside tissue far from surfaces. Biodynamic imaging (BDI) provides the required depth capability, the sensitivity to cellular motions, and the signatures of different dynamical cellular functions. The present disclosure relies on these advantages of BDI to provide a 3D-tissue label-free therapeutic efficacy assay. The multicellular spheroid model is relevant for multicellular resistance (MCR) studies because tumor spheroids are very similar to avascular tumors with heterogeneous hypoxic internal environments characterized by anaerobic glycolysis, acidosis and necrosis. This heterogeneous and hostile internal tumor microenvironment is an incubator for multicellular resistance.
Biodynamic imaging (BDI) is a novel functional imaging approach that penetrates up to 1 mm inside tissue to extract the subcellular motions that define the dynamics and functional responses of living tissues to anti-cancer drugs. It is label-free and non-invasive. The cellular function accessed by tissue-dynamics imaging is not a surrogate monitor of tissue responding to stimuli, but is the actual functioning behavior of the living system. BDI can time-resolve (within 100 msec) changes in these motions as tissues evolve under environmental or pharmacological perturbations. These include organelles transported by ATP-driven molecular motors, actin-myosin-driven membrane undulations, cytoplasmic streaming, telophase and cytokinesis, apoptosis and necrosis, among others. BDI produces unique fingerprints of the action of specific drugs on the motion in specific cell lines. These drug fingerprints give insight into drug mechanisms of action and provide the training set for phenotypic profiling for the classification and discovery of potentially new drugs or new mechanisms of action.
One form of biodynamic imaging it tissue dynamics spectroscopic imaging which is a method that operates on data obtained from holographic optical coherence imaging (OCI). OCI is an optical signal acquisition and processing method which provides three-dimensional images from within an optical scattering medium, e.g., biological tissue. The holographic capture of depth-resolved images from optically thick living tissues has developed through several stages. Optical coherence imaging uses coherence-gated holography to optically section tissue up to 1 mm deep. It is a full-frame imaging approach, closely related to en face optical coherence tomography, but with deeper penetration and high-contrast speckle because of the simultaneous illumination of a broad area. The first implementations of OCI used dynamic holographic media such as photorefractive quantum wells to capture the coherent backscatter and separate it from the high diffuse background.
Digital holography approaches have replaced the dynamic media and have become the mainstay of current implementations of OCI. Highly dynamic speckle was observed in OCI of living tissues caused by dynamic light scattering from the intracellular motions. The dynamic speckle was used directly as an endogenous imaging contrast in motility contrast imaging (MCI) that could track the effects of antimitotic drugs on tissue health.
MCI captures the overall motion inside tissue, but is limited to imaging contrast. The OCI data includes dynamic speckle that is localized from a specified depth within the biological specimen up to 1 mm deep. The technique for isolating dynamic speckle is known including a method for converting the dynamic speckle into time-frequency spectrograms that can be interpreted in terms of biological function and can be applied to phenotypic profiling of drug candidates.
While there has been a considerable amount of improvement of in vitro tissue interrogation through OCI and MCI, there is still an unmet need for an ex vivo imaging arrangement. On difficulty presented by ex vivo imaging is that the optics of the tissue are different than for in vitro tissue. For instance, ex vivo tissue can include blood which can compromise the OCI and MCI imaging.